This time I needed to deploy some custom JAR files to our Hive cluster so that we wouldn’t need to do “ADD JAR” commands in every Hive job (especially useful when using HiveServer API).

Here is the process of adding a custom SerDE or a UDF jar to your Cloudera Hadoop cluster:

First, we have built our JSON SerDe and got a json-serde-1.1.6.jar file.

To make this file available to Hive CLI tools, we need to copy it to /usr/lib/hive/lib on every server in the cluster (I have prepared an rpm package to do just that).

To make sure Hive map-reduce jobs would be able to read/write JSON tables, we needed to copy our JAR file to /usr/lib/hadoop/lib directory on all task tracker servers in the cluster (the same rpm does that).

And last, really important step: To make sure your TaskTracker servers know about the new jar, you need to restart your tasktracker services (we use Cloudera Manager, so that was just a few mouse clicks ;-))

Today, just like many times before, I needed to configure a monitoring server for MySQL using Cacti and awesome Percona Monitoring Templates. The only difference was that this time I wanted to get it to run with 1 min resolution (using ganglia and graphite, both with 10 sec resolution, for all the rest of our monitoring in Swiftype really spoiled me!). And that’s where the usual pain in the ass Cacti configuration gets really amplified by the million things you need to change to make it work. So, this is a short checklist post for those who need to configure a Cacti server with 1 minute resolution and setup Percona Monitoring Plugins on it.

This week, after 3 months in the works, we’ve finally released version 1.7.0 of DbCharmer ruby gem – Rails plugin that significantly extends ActiveRecord’s ability to work with multiple databases and/or database servers by adding features like multiple databases support, master/slave topologies support, sharding, etc.

New features in this release:

Rails 3.0 support. We’ve worked really hard to bring all the features we supported in Rails 2.X to the new version of Rails and now I’m proud that we’ve implemented them all and the implementation looks much cleaner and more universal (all kinds of relations in rails 3 work in exactly the same way and we do not need to implement connection switching for all kinds of weird corner-cases in ActiveRecord).

Forced Slave Reads functionality. Now we could have models with slaves that are not used by default, but could be turned on globally (per-controller, per-action or in a block). This is a new feature that brings our master/slave routing capabilities to a really new level – we could now use it for a really mission-critical models on demand and not be afraid of breaking major functionality of our applications by switching them to slave reads.

Lots of changes were made in the structure of our code and tests to make sure it would be much easier for new developers to understand DbCharmer internals and make changes in its code.

Along with the new release we’ve got a brand new web site. You can find much better, cleaner and, most importantly, correct documentation for the library on the web site. We’ll be adding more examples, will try to add more in-depth explanation of our core functions, etc.

If you have any questions about the release, feel free to ask them in our new mailing list: DbCharmer Users Group.

For more updates on our releases, you can follow @DbCharmer on Twitter.

Back in November 2009 I was working on a project to port Scribd.com code base to Rails 2.2 and noticed that some old plugins we were using in 2.1 were abandoned by their authors. Some of them were just removed from the code base, but one needed a replacement – that was an old plugin called acts_as_readonlyable that helped us to distribute our queries among a cluster of MySQL slaves. There were some alternatives but we didn’t like them for one or another reasons so we’ve decided to go with creating our own ActiveRecord plugin, that would help us scale our databases out. That’s the story behind the first release of DbCharmer.

Today, six months after the first release of the gem and we’ve moved it to gemcutter (which is now the official gems hosting) and we’re already at version 1.6.11. The gem was downloaded more than 2000 times. There are (at least) 10+ large users that rely on this gem to scale their products out. And (this is the most exciting) we’ve added tons of new features to the product.

Here are the main features added since the first release:

Much better multi-database migrations support including default migrations connection changing.

We’ve added ActiveRecord associations preload support that makes it possible to move eager loading queries to the same connection where your finder queries go to.

We’ve improved ActiveRecord’s query logging feature and now you can see what connections your queries executed on (and yes, all those improvements are colorized :-)).

We’ve added an ability to temporary remap any ActiveRecord connections to any other connections for a block of code (really useful when you need to make sure all your queries would go to some non-default slave and you do not want to mess with all your models).

The most interesting change: we’ve implemented some basic sharding functionality in ActiveRecord which currently is being used in production in our application.

As you can see now DbCharmer helps you to do three major scalability tasks in your Rails projects:

Master-Slave clusters to scale out your Rails models reads.

Vertical sharding by moving some of your models to a separate (maybe even dedicated) servers and still keep using AR associations

Horizontal sharding by slicing your models data to pieces and placing those pieces into different databases and/or servers.

So, If you didn’t check DbCharmer out yet and you’re working on some large rails project that is (or going to be) facing scalability problems, go read the docs, download/install the gem and prove them that Rails CAN scale!